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The rise in outdoor temperatures and heatwaves highlights the limitations of buildings in adapting to warming conditions, even in temperate climates. This paper analyses the indoor overheating of residential dwellings in Pamplona (a city in northern Spain, with a Cfb climate) using an urban-scale diagnostic methodology and presents different envelopes' retrofitting scenarios as a strategy to reduce it. The results come from energy simulations conducted during an extremely warm summer in 2022, considering the microclimate effects. The residential typologies most vulnerable to overheating are those with only one orientation, built before the EPBD 2002, and located on top floors. These dwellings show a 23.7% mean of indoor overheating hours (IOH), representing approximately 870 h above the EN 16798-1:2019 adaptive threshold from May to September. Renovating building envelopes to meet current energy standards reduces the IOH by an average of 8.6% and up to 15.35% in the most vulnerable typologies. In the retrofitting scenario with green roof systems, indoor temperatures are up to 0.5 °C lower than when roofs are renovated with traditional systems. This study assists policy-makers in preventing the risk of overheating within cities and encourages them to promote nature-based solutions in order to adapt urban residential buildings and cities to warming conditions. [ABSTRACT FROM AUTHOR]

The dry Mediterranean climate (BShs) is the European region with the highest number of hours of sunshine per year. The high annual solar radiation makes sun shading devices necessary to comply with current energy efficiency standards. However, these standards do not sufficiently consider their effect on the indoor lighting comfort of buildings. The objective is to qualitatively and quantitatively determine how movable sun shading devices jointly influence the energy efficiency, thermal comfort and lighting comfort of buildings in BShs climate. The scientific novelty of the work consists of demonstrating the limitations of the sun shading systems commonly used in southeastern Spain and determining the optimal technical solution in this climate to simultaneously improve thermal and lighting comfort. This research comparatively studies the influence of various movable sun shading systems on the daylighting and thermal performance of an educational building. This study conducted on-site measurements, user surveys and computer simulations to study how to improve the thermal and lighting performances of the building. This work demonstrates that interior solar shading provides little improvement in thermal comfort and reduces the cooling demand by only 25%. External movable sun shading improves thermal comfort and reduces the cooling demand by more than 60%, but only adjustable blinds or awnings achieve adequate and homogeneous illuminance values as they diffuse daylight. The paper concludes that energy efficiency standards should be modified to ensure adequate lighting comfort in buildings. [ABSTRACT FROM AUTHOR]

An effective strategy for sustainable development is to conduct research on vernacular architecture in response to urbanisation as well as environmental and climate change challenges. However, focused discussion has been limited to date due to the diverse range of disciplines involved in vernacular architecture and the unique examples in practice. Scopus, one of the largest literature databases, was used to find and select a total of 1403 documents for this paper. Techniques for both quantitative and qualitative literature analysis were employed using Microsoft Excel (Version 16.75.2) and the visualisation tool VOSviewer (Version 1.6.19). Using bibliometric analysis, more academic publications were reviewed, aiming to analyse the current situation, influence, and future direction of the literature related to vernacular architecture. The current issues have been obtained from the statistical results, and the opportunities and challenges of vernacular architecture in today's cities are discussed. The twenty most frequently referenced publications, keywords, and correlations between co-occurrences were all examined in this bibliometric analysis, along with annual publishing trends and the most influential nations, institutions, sources, and authors. The analysis showed a rising trend in vernacular architectural publications, with China, Italy, and Spain being the most prolific nations whose institutions have a high academic impact. However, the degree of international author collaboration remains insignificant. Future themes could focus on energy, comfort, earthquake resilience, and sustainability, with cultural heritage and vernacular communities still receiving little research attention. This study is a comprehensive bibliometric analysis of vernacular architecture, as well as an important study of sustainability and resilience, affirming the importance of vernacular architecture in terms of future urban form and drawing on the lessons of history. Also, the proposed research framework could be a strong reference for future researchers looking for inspiration. [ABSTRACT FROM AUTHOR]

Climate change represents an important cause of subsidence, especially in coastal cities affected by changes in surface water level and water table. This paper presents a complementary study of Interferometric Synthetic Aperture Radar (InSAR) and Ground Penetrating Radar (GPR) for the early detection of subsidence and sinkhole phenomena. The methodology was applied to a coastal urban area in Galicia, northwest Spain (humid region), showing apparent signs of subsidence and building settlement during the last two years. Two different InSAR methods are compared for the period from June 2021 to March 2022: PSI (Persistent Scatterer Interferometry) and SBAS (Small Baseline Subsets), and the average deformation velocities obtained resulted in −3.0 mm/yr and −4.1 mm/yr, respectively. Additional GPR data were collected in January 2022 to validate the InSAR results, which detected subsidence in agreement with the persistent scatters obtained from the PSI method. This is crucial information to plan preventive maintenance. [ABSTRACT FROM AUTHOR]

Potable water utilities are currently making great efforts to reduce leakage rates and assure long-term supply to the population due to the challenges of climate change, growing population and water shortage scenarios that have been on them over the last years. One of the most employed methods to reduce leakage includes the installation of pressurereducing valves along the water distribution network and the utilization of pressure management schemes. Pressure management includes different types of control models, which are applied according to the requirements of each site. The most advanced and sophisticated scheme is critical point control, which relies on a flow signal from a measuring device or online communication between the critical point and the valve. This paper proposes the utilization of a seasonal autoregressive integrated moving average, or the SARIMA model, to correlate pressure at the outlet of the valve and pressure on the critical point of the area supplied, aiming to set a fixed pressure in the critical point. The SARIMA model is developed according to historical data logged in the field and then validated. Later, the SARIMA model was tested on a real location in the village of Noja, Spain. The analysis of the field test results prove that the proposed model is feasible to be used since there is no significance difference between the target values set in the critical point and the real values measured in the field. The research proves that the SARIMA model can be used as an alternative for critical point control in water distribution networks when no flow signal is available or when communication between the critical point and the pressure reducing valve is not an option. [ABSTRACT FROM AUTHOR]

Due to climate change, hydroclimatic extremes are becoming more frequent and intense and their characterization and analysis is essential for climate modelling. One of the regions that will be most affected by these extremes is the Mediterranean coast of Spain. Therefore, this paper analyses the significant wave height (Hs), peak wave period (Tp) and sea level (SL) extremes and their correlation along the Spanish Mediterranean coast. After conducting this analysis, it is finally concluded that and adjustment of the extreme long-term distribution of Tp is urgently needed to create accurate models and projections, which must be considered in combination with the intense extremes happening in the Levantine basin when modelling this area and designing new projects. [ABSTRACT FROM AUTHOR]

National Parks are spaces that are of great interest for evaluating and monitoring global environmental change as these parks encompass natural, cultural, and rural features, along with ecological processes, which are subject to social or economic changes that are much more difficult to track outside of these spaces. To do this, it is necessary to have a sufficient set of data and indicators to monitor the effects of global change in the short, mid, and long term. The majority of indicators have been developed to monitor the bio-geophysical environment; socio-economic indicators of global change for National Parks are much more limited. The aim of this paper is to present a system of indicators for socio-economic evaluation and monitoring of global change for the Picos de Europa National Park. This park has two unique features: it has one of the two systems of socio-economic indicators developed for the Spanish National Parks, and it is practically the only one of Spain's 16 National Parks with human populations living within its boundaries. Many of the indicators specifically developed for this park can be used for other national parks that have similar characteristics. [ABSTRACT FROM AUTHOR]

Climate change is expected to increase the occurrence of droughts, with the hydrology in alpine systems being largely determined by snow dynamics. In this paper, we propose a methodology to assess the impact of climate change on both meteorological and hydrological droughts, taking into account the dynamics of the snow cover area (SCA). We also analyze the correlation between these types of droughts. We generated ensembles of local climate scenarios based on regional climate models (RCMs) representative of potential future conditions. We considered several sources of uncertainty: different historical climate databases, simulations obtained with several RCMs, and some statistical downscaling techniques. We then used a stochastic weather generator (SWG) to generate multiple climatic series preserving the characteristics of the ensemble scenario. These were simulated within a cellular automata (CA) model to generate multiple SCA future series. They were used to calculate multiple series of meteorological drought indices, the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and a novel hydrological drought index (Standardized Snow Cover Index (SSCI)). Linear correlation analysis was applied to both types of drought to analyze how they propagate and the time delay between them. We applied the proposed methodology to the Sierra Nevada (southern Spain), where we estimated a general increase in meteorological and hydrological drought magnitude and duration for the horizon 2071–2100 under the RCP 8.5 emission scenario. The SCA droughts also revealed a significant increase in drought intensity. The meteorological drought propagation to SCA droughts was reflected in an immediate or short time (1 month), obtaining significant correlations in lower accumulation periods of drought indices (3 and 6 months). This allowed us to obtain information about meteorological drought from SCA deficits and vice versa. [ABSTRACT FROM AUTHOR]

Climate model outputs can be used as climate forcing for hydrological models to study the impact of climate change on the water cycle. This usually propagates cumulative uncertainties, transferring the errors from the climate models to the hydrological models. Then, methodologies are needed to evaluate the impact of climate change at basin scale by reducing the uncertainties involved in the modeling chain. The paper aims to assess the impact of climate change on the runoff, considering a novel approach to build a Regional Climate Model (RCM) ensemble as climate forcing for a parsimonious spatially distributed hydrological model. A semiarid basin of southeast of Spain was selected for the study. The RCM ensembles were built based on seasonal and annual variability of rainfall and temperature. If the runoff projections for 2021–2050 are compared to the 1961–1990 observed period, a significant decrease in runoff equal to -20% (p-value t-test 0.05) was projected. However, by changing the observed period to 1971–2000, a despicable change (2.5%) is identified. This fact demonstrates that trends based on short records are very sensitive to the beginning and end dates, due to the natural variability. Special attention should be paid to the selection of the period for impact studies. [ABSTRACT FROM AUTHOR]

Water scarcity will increase in the world in the coming decades due to climate change, especially in areas that currently already have water scarcity, such as the Mediterranean area. In these areas, to guarantee water resources, systems' sustainability is necessary to improve demand management and the development of non-conventional resources, such as treated wastewater reuse or seawater desalination. These non-conventional resources are highly energy-consuming; so, reducing energy costs is a key element in developing their use in different sectors, including agriculture. Combining photovoltaic solar energy with seawater desalination by reverse osmosis will reduce the cost of producing water to below 0.36 EUR/m3; so, this resource can be attractive for agriculture, as demonstrated in this work. The arrangement of bifacial solar modules in horizontal single-axis tracking systems increases the energy amount generated from the sun in one hour or more, improving the facility's efficiency and reducing the desalinated water cost. The greater distance between the solar module lines, with a ground coverage ratio (GCR) = 0.3, makes for a better environmental integration of the facility and allows the development of agrovoltaic strategies, such as native flora planting and pollinator colonization. [ABSTRACT FROM AUTHOR]

Planning a well-structured urban green infrastructure (UGI) is essential for cities to counteract the impacts of climate change. Soil carbon and air temperature differences between open and plant-covered sites were used as proxies of carbon sequestration (CS) and temperature regulation (TR) to evaluate the current conditions of UGI in Zaragoza, a medium-sized city in northeastern Spain. Alternative scenarios were constructed, after a stakeholder consultation, at both city and municipal (city plus peri-urban zone) scales, extrapolating the highest values of CS and TR to two groups of UGI types grouped based on the state of their ecological functioning. We employed analysis of variance to compare mean values of CS and TR across diverse scenarios at both city and municipality scales. Statistically significant differences were found in city-scale and municipality-scale scenarios for both CS and TR. Multiplying CS by area did not show significant variation in city scale. Significant differences were found when multiplying TR by area at both scales, with exceptions in certain scenario combinations. These results suggest favoring the restoration of UGI sites in peri-urban zones (such as forests and steppe zones) to increase CS and those in densely urbanized zones (such as urban parks) to provide TR benefits. [ABSTRACT FROM AUTHOR]

The energy crisis and the exacerbation of climate change, along with the associated geopolitical tensions, including the war in Ukraine, are accelerating the energy transition in Europe. A transition from fossil energy sources to renewable energy sources that have a low Energy Return Rate, involves, among many other issues, the use of wide areas to locate the necessary infrastructure for production, transport and storage, altering territories with agricultural, cultural and ecological values. This process is based on the deployment of renewable energy megaprojects in peripheric areas of the continent, mostly in the southern states creating a wide range of social conflicts and resistances. We analyse this process in the case study of the province of Granada, a peripheric territory of south-east Spain considering the category of energy colonialism and the six dimensions that characterise it, arguing that this is a proper approach to address internal colonialism related to the corporate energy transition. We also want to demonstrate the importance of using participatory methodologies for this analysis, so we have developed an online survey, semi-structured interviews and participatory cartography workshops, always focusing on the citizens and stakeholders who are resisting the deployment of renewable energy megaprojects in the province of Granada. The obtained results allow us to confirm the necessity of using participatory methodologies and the colonial aspect of this deployment, including the characteristics of social resistance, the territorial impacts, the land-grabbing process and the inequalities in the production, distribution and use of energy. We conclude with the need to articulate a decolonial energy transition where participatory methods constitute a fundamental tool both to attend the resistances and to build the alternatives. [ABSTRACT FROM AUTHOR]

There is growing concern that climate change poses a serious threat to the sustainability of the insurance business. Understanding whether climate warming is a cause for an increase in claims and losses, and how this cause–effect relationship will develop in the future, are two significant open questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We quantify climate change using the Spanish Actuarial Climate Index (SACI). We utilize a database containing all the claims resulting from hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, the monthly number of loss costs equal to one, and the monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We attempt to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change, as measured by the SACI, explains these three dependent variables. We also provide an estimate of the increase in the monthly total losses' Value at Risk, corresponding to a future increase in climate change measured in units of the SACI. Spanish crop insurance managers should carefully consider these conclusions in their decision-making process to ensure the sustainability of this line of business in the future. [ABSTRACT FROM AUTHOR]

Wind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France. [ABSTRACT FROM AUTHOR]

The degree of success of river water diversion planning decisions is affected by uncertain environmental conditions. The adaptive water management framework incorporates this uncertainty at all stages of management. While the most effective form of adaptive management requires experimental comparison of practices, the use of optimization modeling is convenient for conducting exploratory simulations to evaluate the spatiotemporal implications of current water diversion management decisions under future environmental changes. We demonstrate such an explorative modeling approach by assessing river water availability for diversion in a river basin in Northern Spain under two future environmental scenarios that combine climate and land use change. An evolutionary optimization method is applied to identify and reduce trade-offs with Supporting Ecosystem Services linked to environmental flow requirements for relevant local freshwater species. The results show that seasonal shifts and spatial heterogeneity of diversion volumes are the main challenges for the future diversion management of the Pas River. Basin-scale diversion management should take into account the seasonal planning horizon and the setting of tailored diversion targets at the local-level to promote the implementation of adaptive management. The presented assessment can help with strategic placement of diversion points and timing of withdrawals, but it also provides deeper insight into how optimisation can support decision-making in managing water diversion under uncertain future environmental conditions. [ABSTRACT FROM AUTHOR]

A good understanding of historical change rates is a key requirement for effective coastal zone management and reliable predictions of shoreline evolution. Historical shoreline erosion for the coast of Guardamar del Segura (Alicante, Spain) is analyzed based on aerial photographs dating from 1930 to 2022 using the Digital Shoreline Analysis System (DSAS). This area is of special interest because the construction of a breakwater in the 1990s, which channels the mouth of the Segura River, has caused a change in coastal behavior. The prediction of future shorelines is conducted up to the year 2040 using two models based on data analysis techniques: the extrapolation of historical data (including the uncertainty of the historical measurements) and the Bruun-type model (considering the effect of sea level rises). The extrapolation of the natural erosion of the area up to 1989 is also compared with the reality, already affected by anthropic actions, in the years 2005 and 2022. The construction of the breakwater has accelerated the erosion along the coast downstream of this infrastructure by about 260%, endangering several houses that are located on the beach itself. The estimation models predict transects with erosions ranging from centimeters (±70 cm) to tens of meters (±30 m). However, both models are often overlapping, which gives a band where the shoreline may be thought to be in the future. The extrapolation of erosion up to 1989, and its subsequent comparison, shows that in most of the study areas, anthropic actions have increased erosion, reaching values of more than 35 m of shoreline loss. The effect of anthropic actions on the coast is also analyzed on the housing on the beach of Babilonia, which has lost around 17% of its built-up area in 40 years. This work demonstrates the importance of historical analysis and predictions before making any significant changes in coastal areas to develop sustainable plans for coastal area management. [ABSTRACT FROM AUTHOR]

Simple Summary: The artisanal octopus fishery is a great tradition and has a large economic impact in Northern Spain. Despite its importance, there is scarce genetic information for this exploited population. The uniqueness of an exploited population and the effects that exploitation may have on its long-term survival is essential information that can be obtained by studying the past and current spatial and temporal genetic patterns. The mitochondrial DNA is used here as a genetic tool to gain insight into Northeast Atlantic octopus populations and their evolutionary history. Although it is not sensitive enough to detect differences in nearby populations, it allows us to differentiate the two main lineages that originated during the Quaternary glaciations. One of the lineages is present exclusively in northern latitudes and the other mainly in the south, although, for the first time, its presence is demonstrated also in the north of the Iberian Peninsula. This implies a more continuous distribution than previously thought for this lineage. We also detect temporal changes in the distribution of the two lineages in contact zones. These changes seem to be associated with the effect of changing oceanographic conditions. Future studies on these associations could be of interest for fisheries in the scenario of global climate change. Octopus vulgaris is one of the most harvested octopus species in the world. In the Iberian Peninsula, there are several small-scale fisheries that have a long-term tradition of harvesting octopus. The Asturias fleet (in Northern Spain) has an internationally recognized MSC label for its exploitation. Of concern, genetic assessments of exploited stocks are currently scarce, which could prevent the implementation of adequate managing strategies. We use two mitochondrial regions (cytochrome oxidase subunit 1 and control region) to analyze the genetic status and evolutionary events that conditioned octopus populations' characteristics in the Northeastern Atlantic. A total of 90 individuals were sampled from three different localities in the Iberian Peninsula as well as a location in Macaronesia. Temporal genetic analyses on Asturias and Algarve populations were also performed. Results indicated the absence of fine spatial genetic structuring but showed the Canary Islands (in Macaronesia) as the most distinct population. Our analyses detected two distinct clades, already described in the literature, but, for the first time, we confirmed the presence of the α-southern haplogroup in the Northern Iberian Peninsula. This result indicates a more continuous cline for the distribution of these two haplogroups than previously reported. Temporal changes in the distribution of both haplogroups in contact zones were also detected. [ABSTRACT FROM AUTHOR]

Climate change will have a great impact on the hottest climates of southern Europe and the existing residential stock will be extremely vulnerable to these future climatic conditions. Therefore, there is an urgent need to update this building stock considering imminent global warming by applying climatic files that predict future conditions in building performance simulations. This research makes use of the two most applied tools (Meteonorm and CCWorldWeatherGen) for generating future climate hourly datasets for 2050 and 2080 in southern Spain. The results predicted for outdoor and indoor thermal conditions and cooling and heating demands are evaluated for two different scale simulation models: a test cell and a multi-family building located in southern Spain. The main aim of this work is the development of a comparative analysis of the results to highlight their potential differences and raise awareness of the influence of the climate data projection method on the simulation outcome. The results show that the projection method selected for producing future climatic files has relevant effects on the analysis of thermal comfort and energy demand, but it is considerably reduced when an annual evaluation is developed. [ABSTRACT FROM AUTHOR]

Marine ecosystems are among the richest in terms of biodiversity, and at present, still remain largely unknown today. In the molecular biology era, several analyses have been conducted to unravel the biological processes in this ecosystem. These systems have provided biotechnological solutions to current problems, including the treatment of diseases, as well as for the development of new biotechnological tools with applications in biomedicine and/or agri-food. In addition, in the context of climate change and global warming, these studies become even more necessary for the development of molecular tools that allow a reliable follow-up of this situation to anticipate alterations and responses of bioindicator species and to create a database to prevent and predict the environmental and climatic changes before the damage is irreversible. Proteomics approaches have revealed their potential use to obtain the set of biological effectors that lead to the real biological station on a specific stage, the proteins. In addition, proteomics-based algorithms have allowed the discovery of proteins with new potential biotechnological applications from proteome data through "applied proteomics". In this project, the first proteome analysis of the sea anemone, Anemonia sulcata, and its symbiont has been developed. These organisms present a wide distribution sea ecosystem. In Spain, it is accepted as a fishing and aquaculture species. Moreover, Anemonia sulcate has a symbiotic relation with autotroph Dinoflagellates, Symbiodinium spp., that allows the study of its relation at the molecular level. For the first characterization of A. sulcata proteome, three independent biological replicates were used, and proteins were extracted and analyzed by LC–MS/MS, allowing the quantification of 325 proteins, 81 from Symbiodinium spp. proteins and 244 from A. sulcata proteins. These proteins were subjected to gene ontology categorization by Cellular Component, Molecular Function and Biological Process. These analyzes have allowed the identification of biomarkers of gene expression as potential powerful emerging diagnostic tools to identify and characterize the molecular drivers of climate change stresses and improve monitoring techniques. In addition, through the application of novel algorithms for the detection of bioactive compounds based on the analysis of molecules of marine origin, the proteome has allowed the identification of proteins with potential applications in the fields of biomedicine and agri-food. [ABSTRACT FROM AUTHOR]

This work proposes a methodological approach applied to ephemeral gravel-bed streams to verify the change in the magnitude and frequency of hydrological events affecting the morphological dynamics and sediment budget in this type of channel. For the case study, the Azohía Rambla, located in southeastern Spain, was chosen, emphasizing the research on two reference riverbed sections (RCRs): an upper one, with a predominance of erosion, and a middle one, where processes of incision, transport, and deposition were involved. First, this approach focuses on relationships between peak discharges and sediment budgets during the period 2018–2022. For this purpose, water level measurements from pressure sensors, a One-Dimensional Hydrodynamic model, and findings from comparative analyses of high-resolution differential digital elevation models (HRDEM of Difference-HRDoD) based on SfM-MVS and LiDAR datasets were used. In a second phase, the GeoWEPP model was applied to the period 1996–2022 in order to simulate runoff and sediment yield at the event scale for the watersheds draining into both RCRs. During the calibration phase, a sensitivity analysis was carried out to detect the most influential parameters in the model and confirm its capacity to simulate peak flow and sediment delivery in the area described above. Values of NS (Nash–Sutcliffe efficiency) and PBIAS (percent bias) equal to 0.86 and 7.81%, respectively, were found in the calibration period, while these indices were 0.81 and −4.1% in the validation period. Finally, different event class patterns (ECPs) were established for the monitoring period (2018–2022), according to flow stage and morphological channel adjustments (overtopping, bankfull and sub-bankfull, and half-sub-bankfull), and then retrospectively extrapolated to stages of the prior simulated period (1996–2018) from their typical sequences (PECPs). The results revealed a significant increase in the number of events and PECPs leading to lower bed incision rates and higher vertical accretion, which denotes a progressive increase in bed armoring and bank erosion processes. [ABSTRACT FROM AUTHOR]

Treated wastewater is constantly produced and relatively unaffected by climatic conditions, while Constructed Wetlands (CWs) are recognized as green technology and a cost-effective alternative to improve treated wastewater quality standards. This paper analyses how farmers consider (1) treated wastewater to face water scarcity risk and (2) CW as mechanisms to face agricultural water pollution in a climate change adaptation context. A survey about climate change perception and adaptation measures was answered by 177 farmers from two irrigation communities near El Hondo coastal wetland and the Santa Pola saltmarshes, both perceived as natural-constructed systems in Alicante, southern Spain. Results highlighted how, even with poor-quality standards, treated wastewater is considered a non-riskier measure and more reliable option when addressing climate change impacts. Overall, physical water harvesting (such as CWs) is the favorite choice when investing in water technologies, being perceived as the best option for users of treated wastewater and those concerned about water quality standards. Consequently, CWs were recognized as mechanisms to increase water supply and reduce water pollution. Policy-makers and water managers can use these learnings from farmers' experience to identify the main barriers and benefits of using treated wastewater and CWs to address water scarcity and water pollution risks. [ABSTRACT FROM AUTHOR]

The Mediterranean region is a climate change hotspot, especially concerning issues of hydrological planning and urban water supply systems. In this context, the Jucar River Basin (Spain) presents an increase of frequency, intensity and duration of extreme meteorological phenomena, such as torrential rains, droughts or heat waves, which directly affect the quantity and quality of raw water available for drinking. This paper aims to analyze the effects of climate change on the raw water quality of the Jucar River Basin District, which mainly supplies the city of Valencia and its metropolitan area, in order to adapt drinking water treatments to new conditions and opportunities. For this purpose, we used observed data of water quality parameters from four stations and climate drivers from seven Earth system models of the latest Coupled Model Intercomparison Project—Phase 6. To model water quality (turbidity and conductivity) in the past and future scenarios, this study employs a backward stepwise regression taking into account daily values of mean temperature, maximum temperature, total rainfall and minimum and maximum relative humidity. Results showed that the model performance of the water quality simulation is more adequate for short moving-average windows (about 2–7 days) for turbidity and longer windows (about 30–60 days) for conductivity. Concerning the future scenarios, the most significant change was found in the projected increase of conductivity for the station of the Júcar river, between 4 and 11% by 2100, respectively, under the medium (SSP2–4.5) and pessimistic (SSP5–8.5) emission scenarios. The joint use of these types of management and monitoring tools may help the managers in charge of carrying out the different water treatments needed to apply a better plan to raw water and may help them identify future threats and investment needs to adapt the urban water supply systems to the changing conditions of raw water, such as turbidity or conductivity, as a consequence of climate change. [ABSTRACT FROM AUTHOR]

Currently, there is a lack of accurate simulation tools for the thermal performance modeling of courtyards due to their intricate thermodynamics. Machine Learning (ML) models have previously been used to predict and evaluate the structural performance of buildings as a means of solving complex mathematical problems. Nevertheless, the microclimatic conditions of the building surroundings have not been as thoroughly addressed by these methodologies. To this end, in this paper, the adaptation of ML techniques as a more comprehensive methodology to fill this research gap, covering not only the prediction of the courtyard microclimate but also the interpretation of experimental data and pattern recognition, is proposed. Accordingly, based on the climate zoning and aspect ratios of 32 monitored case studies located in the South of Spain, the Support Vector Regression (SVR) method was applied to predict the measured temperature inside the courtyard. The results provided by this strategy showed good accuracy when compared to monitored data. In particular, for two representative case studies, if the daytime slot with the highest urban overheating is considered, the relative error is almost below 0.05%. Additionally, values for statistical parameters are in good agreement with other studies in the literature, which use more computationally expensive CFD models and show more accuracy than existing commercial tools. [ABSTRACT FROM AUTHOR]

In this study, we utilized three different indices to assess drought conditions in the Doñana National Park (DNP) located in southern Spain. These indices included the Standardized Precipitation Index (SPI), which is based on precipitation statistics, the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates both precipitation and air temperature data, and the Groundwater Recharge Drought Index (GRDI), a newly developed index specifically designed to evaluate groundwater drought. The analysis covered the time period from 1985 to 2015, and future projections were made for the years 2030–2060 under different climate scenarios (RCP 4.5 and RCP 8.5). Our findings revealed a significant decrease in total precipitation of approximately 13–14% compared to historical records (1985–2015). Moreover, severely to extremely wet periods exhibited a reduction ranging from 25% to 38%. A key contribution of this study is the application of the GRDI index, which allowed us to assess groundwater recharge rates. We observed a decline in the simulated mean recharge rates during the 21st century when compared to the historical period spanning from 1950 to 2009. This decline can be attributed to increased evapotranspiration. The results of this research provide valuable insights for the Spanish water resources administration. The observed reductions in precipitation and groundwater recharge rates emphasize the need for appropriate mitigation measures. The findings will aid the administration in formulating an integrated water resources management strategy in the Doñana National Park and its surrounding basin. By understanding the projected changes in drought conditions, the administration can make informed decisions to ensure sustainable water resource management in the region. [ABSTRACT FROM AUTHOR]

Featured Application: Pistachio orchard management using remote sensing with UAVs. Pistachio (Pistacia vera L.) has earned recognition as a significant crop due to its unique nutrient composition and its adaptability to the growing threat of climate change. Consequently, the utilization of remote sensing techniques for non-invasive pistachio monitoring has become critically important. This research was conducted in two pistachio orchards located in Spain, aiming to assess the effectiveness of vegetation indices (VIs) in estimating nut yield and quality under various irrigation conditions. To this end, high-resolution multispectral and thermal imagery were gathered using a Micasense ALTUM sensor carried by a DJI Inspire 2 drone in order to calculate the NDRE (normalized difference red edge index), GNDVI (green normalized difference vegetation index), NDVI (normalized difference vegetation index), and CWSI (crop water stress index). Each orchard underwent two flights at distinct growth stages, totaling four flights. In June, NDRE-carbohydrates (r = 0.78) and CWSI-oleic (r = 0.77) showed the highest correlations, while in September, CWSI-carbohydrates (r = 0.62) and NDVI-iron (r = 0.54) Despite NDVI's limitations due to saturation effects, all VIs had significant yield and quality correlations, with GNDVI proving most effective in both flights. CWSI correlated considerably on both dates in terms of several quality parameters (carbohydrate percentage, magnesium, iron, and fatty acids, namely palmitoyl, stearic, oleic, and linoleic), surpassing non-thermal indices. Finally, it is important to consider the impact of environmental factors, such as the location of the sun, when interpreting the CWSI, as it modifies the temperature distribution pattern within the canopy. This study supports the viability of remote sensing and vegetation indices as potential tools for enhancing the management of pistachio orchards. [ABSTRACT FROM AUTHOR]

The construction sector has an important role to play in reducing the threat of climate change. Thus, this work proposes, analyses, and compares two constructive strategies for the intervention/rehabilitation of a protected building located in Seville (Spain). The first solution intends to follow traditional techniques and standardized criteria, while the second option takes into account environmental aspects for the constructive definition of the proposal. An environmental study of each constructive solution, using a life-cycle assessment methodology, as well as an energy behavior analysis were carried out. The results show that the "sustainable proposal" represents a significant environmental improvement, in which a reduction in CO2 emissions and incorporated energy can be appreciated apart from an optimal energy certification. Finally, the sustainable proposal reveals a significant economic reduction in the total budget of the intervention. [ABSTRACT FROM AUTHOR]

Atlantic salmon Salmo salar supports highly valuable commercial and recreational fisheries in Europe, but its stocks are currently overexploited and threatened by climate change. Its southernmost populations (in northern Spain) play a key role in conserving the species' original genetic diversity, which is endangered due to decades-long (1970s to 1990s) massive stocking with non-native stocks. Their decline is well documented, but the effect of stock transfer and conservation efforts is unclear. Nine microsatellite loci were amplified from archival samples (scales from 1958–1959) from eight Spanish rivers to analyse the species' natural genetic dynamics before its decline started. Allelic richness was high in the historical populations (the 1950s) and above most contemporary estimates. Private alleles were found in most rivers, indicating high local uniqueness and relative isolation among river basins. Some alleles are regional markers since they are rare or absent from contemporary northern European populations. Effective population size suggested good conservation status, with higher values than those estimated for contemporary populations. Strong population structure and genetic differentiation between rivers were found, with limited gene flow, restricted to geographically close populations. Our estimates of historical genetic diversity and structure from southernmost salmon populations are a powerful benchmark to guide conservation programs. [ABSTRACT FROM AUTHOR]

Walkability is a modern concept that has become important in recent years due to the doubtless effects it has on aspects such as health and wellbeing, sustainable development, climate change, and tourism. It is necessary, therefore, that urban development strategies aim to achieve walkable cities. The main objective of this study is to define a methodology to calculate the walkability index in tourist cities and to predict the effects of climate change on this index, which is applied to three World Heritage cities in central Spain: Salamanca, Ávila, and Segovia. The methodology is developed in three phases. Phase I focus on the calculation of walkability, considering the following factors: facilities and services, accessibility, sidewalk width, population density, green areas, and urban trees. In Phase II, walkability in 2020, climate-related variables were added to the previous result: temperatures, solar radiation, and shadows. Finally, the third phase, walkability under climate change pressure in 2030, 2050, and 2100, establish predictions for different climate scenarios. The results show excellent walkability indices (higher) in city centers and newly built neighborhoods and low values in the rest of the peripheral areas, industrial estates, and neighborhoods. Climate predictions showed a generalized decrease in walkability over time, even higher in the scenario with high greenhouse gas emissions. Likewise, the models can be an excellent tool for the tourist management of cities since they show the most walkable areas and, therefore, the most suitable for tourist routes. [ABSTRACT FROM AUTHOR]

Background: Heatwaves have become a public health emergency raising great public health concerns. Correspondingly, due to climate change, the increase in extreme weather events, such as heatwaves, floods and hurricanes, is predicted through state-of-the-art models and robust statistical analyses. Since the Mediterranean basin is recognized as the most prominent global climate change hot spot, further scientific research on the future impacts of heatwaves on human mortality, as well as human health and well-being, in the Mediterranean region is critical. Methods: The aim of the present study is to compare the relationship between three different causes of mortality (i.e., cardiological, respiratory and cardiorespiratory) and temperature between two countries (Spain and Greece) and five cities (i.e., Madrid, Barcelona, Valencia, Attica and Thessaloniki). To compare the five cities under examination, a robust statistical methodological framework (i.e., Threshold Regression Analysis (TRA)) was applied so as to examine the critical value above which the mean temperature affects cardiological, respiratory and cardiorespiratory mortality. Results: Our results prove that the relationship between mortality and temperature is a nonlinear relationship shaping a U- or J-shaped curve, meaning that mortality is affected by temperature in a non-constant way, indicating that mortality increases during both low and high temperatures. Conclusions: By calculating different temperature thresholds for the five cities under examination, we show that different temperature thresholds are more accurate for different climatic conditions. Hence, climatic conditions should be taken into account when examining the impacts of temperature on human health. [ABSTRACT FROM AUTHOR]

Coasts worldwide face a great variety of environmental impacts, as well as increased anthropogenic pressures due to urbanization and rapid population growth. Human activities menace ecosystem services and the economy of coastal countries, often based on "Sun, Sea and Sand" (3S) tourism. The five parameters of greatest importance (the "Big Five") for beach visitors are safety, facilities, water quality, no litter and scenery, and the characterization of the latter was recently carried out by means of a checklist of 26 natural and human parameters, parameter weighting matrices and fuzzy logic, according to the "Coastal Scenic Evaluation System" (CSES) methodology. In order to propose sound coastal management strategies, the main aim of this paper is to propose a method to determine the scenic sensitivity of (i) natural parameters to coastal natural processes in a Climate Change context and (ii) human parameters to visitors' pressure in a scenario of increasing tourism and coastal developments. Regarding natural parameters, the sensitivity of "Beach face" and "Dunes" parameters is determined according to an Erodibility Index with a Correction Factor, taking into account wave forcing characteristics, tidal range and trends at a local scale of Sea Level Rise and Storm Surge. This establishes a Sensitivity Index to natural processes. A site's scenic sensitivity to human pressure/activities was determined by considering the sensitivity of several human parameters of the CSES method according to beach typology and access difficulty together with the Protection Area Management Category to which a site belongs. A Human Impact Index is obtained, which is afterwards corrected by taking into account local trends of tourism pressure, establishing a Sensitivity Index to human pressure. Finally, a total Sensitivity Index considering both natural processes and human pressure is obtained, and sites divided into three sensitive groups. The results can be useful to limit and prevent environmental degradation linked to natural processes and tourism development, and also to suggest measures to improve the scenic value of investigated sites and their sustainable usage. The method was tested for 29 sites of great scenic quality along the Mediterranean coast of Andalusia, Spain. [ABSTRACT FROM AUTHOR]

The management of droughts is a challenging issue, especially in water scarcity areas, where this problem will be exacerbated in the future. The aim of this paper is to identify potential groundwater (GW) bodies with reduced vulnerability to pumping, which can be used as buffer values to define sustainable conjunctive use management during droughts. Assuming that the long term natural mean reserves are maintained, a preliminary assessment of GW vulnerability can be obtained by using the natural turnover time (T) index, defined in each GW body as the storage capacity (S) divided by the recharge (R). Aquifers where R is close to S are extremely vulnerable to exploitation. This approach will be applied in the 146 Spanish GW bodies at risk of not achieving the Water Framework Directive (WFD objectives, to maintain a good quantitative status. The analyses will be focused on the impacts of the climate drivers on the mean T value for Historical and potential future scenarios, assuming that the Land Use and Land Cover (LULC) changes and the management strategies will allow maintenance of the long term mean natural GW body reserves. Around 26.9% of these GW bodies show low vulnerability to pumping, when viewing historical T values over 100 years, this percentage growing to 33.1% in near future horizon values (until 2045). The results show a significant heterogeneity. The range of variability for the historical T values is around 3700 years, which also increases in the near future to 4200 years. These T indices will change in future horizons, and, therefore, the potential of GW resources to undergo sustainable strategies to adapt to climate change will also change accordingly, making it necessary to apply adaptive management strategies. [ABSTRACT FROM AUTHOR]

(1) Background: In agro-ecosystems, the success of the crops has a strong connection to biodiversity in the landscape. In the face of climate change, it is important to understand the response to environmental variation of weed species by means of their distribution. In the last century, biodiversity has been impacted due to a variety of stresses related to climate change. Although the composition of vegetation tends to change at a slower rate than climate change, we hypothesize species present in weed communities are distributed in diverse patterns as a response to the climate. Therefore, the general aim of this paper is to investigate the effect of temperature, using latitude as an indicator, on the composition and distribution of weed communities in agro-ecosystems. (2) Methods: Weeds were monitored in georeferenced cereal fields which spanned south and central Spanish regions. The graphic representation according to latitude allowed us to identify groups of weeds and associate them to a temperature range. We classified weeds as generalist, regional, or local according to the range of distribution. (3) Results: The monitoring of species led to the classification of weeds as generalist, regional or local species according to latitude and associated temperature ranges. Three weed species that were present in all latitude/temperature regions, were classified as generalist (Linaria micrantha (Cav) Hoffmanns & Link, Sonchus oleraceous L., and Sysimbrium irium L.). The species were classified as regional or local when their presence was limited to restricted latitude/temperature ranges. One weed, Stellaria media (L.) Vill., was considered a local species and its distribution dynamics can be considered an indicator of temperature. (4) Conclusions: The novel methodology used in this study to assign weed distribution as an indicator of climatic conditions could be applied to evaluate climate gradients around the world. [ABSTRACT FROM AUTHOR]

Floods are one of the natural hazards that could be most affected by climate change, causing great economic damage and casualties in the world. On December 2019 in Reinosa (Cantabria, Spain), took place one of the worst floods in memory. Implementation of DIRECTIVE 2007/60/EC for the assessment and management of flood risks in Spain enabled the detection of this river basin with a potential significant flood risk via a preliminary flood risk assessment, and flood hazard and flood risk maps were developed. The main objective of this paper is to present a methodology to estimate climate change's effects on flood hazard and flood risk, with Reinosa as the case study. This river basin is affected by the snow phenomenon, even more sensitive to climate change. Using different climate models, regarding a scenario of comparatively high greenhouse gas emissions (RCP8.5), with daily temperature and precipitation data from years 2007–2070, and comparing results in relative terms, flow rate and flood risk variation due to climate change are estimated. In the specific case of Reinosa, the MRI-CGCM3 model shows that climate change will cause a significant increase of potential affected inhabitants and economic damage due to flood risk. This evaluation enables us to define mitigation actions in terms of cost–benefit analysis and prioritize the ones that should be included in flood risk management plans. [ABSTRACT FROM AUTHOR]

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations. [ABSTRACT FROM AUTHOR]

Simple Summary: Two new representatives of the blattinopsid genus Glaphyrophlebia, from the Gzhelian of Southern France and Spain, respectively, are described and illustrated. They suggest that the diversity of this genus began to increase during the latest Carboniferous, possibly in relation to the climatic changes occurring at that time. Glaphyrophlebia victoiriensis sp. nov. (Paoliida: Blattinopsidae) is the third Gzhelian representative of the genus and is described based on a beautiful forewing from the Var department in Southern France. Together with the description of another forewing fragment of a Glaphyrophlebia sp. from the Province of León in NW Spain, they improve our knowledge of fossil insects from French and Spanish upper Carboniferous deposits. The specimen of Glaphyrophlebia sp. is the first mention of the family in the Carboniferous of Spain and extends the geographical distribution of the genus. These descriptions suggest that the genus Glaphyrophlebia was speciose during the Upper Pennsylvanian, while otherwise very diverse in the lower and middle Permian strata of the Russian Federation. We proposed the first hypothesis to explain the diversification of the family and of its most speciose genera and to argue that their diversity dynamics were likely linked with the major environmental changes that followed the collapse of the Carboniferous rainforest, notably the extension of arid biomes during the Permian period. The exquisite preservation and the fineness of the sediment from Tante Victoire, in which the new species was found, suggests that the locality is suitable for preserving other fossil insects and will require additional investigations. [ABSTRACT FROM AUTHOR]

In view of heightened climate change (CC), adaptation strategies are imperative to diminish the impacts on social and environmental assets. Two approaches are commonly used to formulate adaptation measures, namely bottom-up and top-down, each with inherited limitations. A sound bridge between both approaches is low-regret adaptive measures, which result in win-win scenarios, as they provide solutions to current pressures and contribute to building CC adaptive capacity. Managed aquifer recharge (MAR) is a term that includes a series of techniques that enhance groundwater storage for later use or environmental purposes. MAR is often mentioned in the literature as a CC adaptation measure. Nonetheless, few examples explicitly prove this point. We show through the Los Arenales MAR systems (Central Spain) that MAR is a low-regret CC adaptive measure. We evaluate a series of social and environmental challenges that MAR systems contribute to solving, as well as their attributes that diminish the expected impacts of CC in the study area. MAR in the Los Arenales groundwater body has resulted in an overall increase in groundwater levels; a reduction in groundwater pumping energy and costs and CO2 emissions; restoration of a surface water body; improvement in rural population indexes; and enhanced groundwater demand control and CC adaptive capacity through irrigation communities. To cope with CC, the Los Arenales MAR systems can be operated even if decreasing streamflow precludes the use of river water surpluses; they provide surface storage volume to mitigate flooding; and they decrease the impacts of droughts and water scarcity. This research proves that MAR is a water management tool capable of providing solutions to several pressures simultaneously in the present and future, an attribute particularly useful when dealing with adaptation gaps in developing countries, rural areas, or regions lacking long-term climatic data. [ABSTRACT FROM AUTHOR]

The Climate Change scenario projected by the IPCC for the year 2050 predicts noticeable increases in temperature. In severe summer climates, such as the Mediterranean area, this would have very negative effects on thermal comfort in the existing housing stock, given the current high percentage of dwellings which are obsolete in energy terms and house a population at serious risk of energy poverty. The main aim of this paper is to generate a predictive model in order to assess the impact of this future climate scenario on thermal comfort conditions in an entire building category. To do so, calibrated models representing linear-type social multi-family buildings, dating from the post-war period and located in southern Spain, will be simulated extensively using transient energy analyses performed by EnergyPlus. In addition, a sensitivity analysis will be performed to identify the most influential parameters on thermal discomfort. The main results predict a generalized deterioration in indoor thermal comfort conditions due to global warming, increasing the average percentage of discomfort hours during the summer by more than 35%. This characterization of the future thermal behaviour of the residential stock in southern Spain could be a trustworthy tool for decision-making in energy retrofitting projects which are so badly needed. To do so, further work is required on some limitations of this model so that different user profiles and typologies can be represented in detail and an economic assessment can be included. [ABSTRACT FROM AUTHOR]

Environmental awareness of the ecological problems caused by this climate crisis and its impact on global health has been growing globally. Nurses are health care agents that usually hurt the environment and contribute to the unsustainability of the care system. Such behavior is perpetuated without the nurses' awareness and is even magnified by the current pandemic, jeopardizing the health systems and the Sustainable Development Goals. However, there is no Spanish version of any survey that measures the awareness of these agents, only the Nurses Environmental Awareness Tool (NEAT) is available. The current research presents a unique investigation based on a mixed method, using the Spanish version of the NEAT, also called NEAT-es. The results of the mixed analysis (N = 376), a cognitive interview, and descriptive analysis indicated perfect consistency (Cronbach's alpha > 0.80), better than the original. The survey validation achieved higher values and can be used to measure environmental awareness in Spain and Spanish-speaking countries. [ABSTRACT FROM AUTHOR]

Proactive silviculture treatments (e.g., thinning) may increase C sequestration contributing to climate change mitigation, although, there are still questions about this effect in Mediterranean pine forests. The aim of this research was to quantify the storage of biomass and soil organic carbon in Pinus forests along a climatic gradient from North to South of the Iberian Peninsula. Nine experimental Pinus spp trials were selected along a latitudinal gradient from the pre-Pyrenees to southern Spain. At each location, a homogeneous area was used as the operational scale, and three thinning intensity treatments: unthinned or control (C), intermediate thinning (LT, removal of 30–40% of the initial basal area) and heavy thinning (HT, removal of 50–60%) were conducted. Growth per unit area (e.g., expressed as basal area increment-BAI), biomass, and Soil Organic Carbon (SOC) were measured as well as three sets of environmental variables (climate, soil water availability and soil chemical and physical characteristics). One-way ANOVA and Structural Equation Modelling (SEM) were used to study the effect of thinning and environmental variables on C sequestration. Biomass and growth per unit area were higher in the control than in the thinning treatments, although differences were only significant for P. halepensis. Radial growth recovered after thinning in all species, but it was faster in the HT treatments. Soil organic carbon (SOC10, 0–10 cm depth) was higher in the HT treatments for P. halepensis and P. sylvestris, but not for P. nigra. SEM showed that Pinus stands of the studied species were beneficed by HT thinning, recovering their growth quickly. The resulting model explained 72% of the variation in SOC10 content, and 89% of the variation in silvicultural condition (basal area and density) after thinning. SOC10 was better related to climate than to silvicultural treatments. On the other hand, soil chemical and physical characteristics did not show significant influence over SOC10- Soil water availability was the latent variable with the highest influence over SOC10. This work is a new contribution that shows the need for forest managers to integrate silviculture and C sequestration in Mediterranean pine plantations. [ABSTRACT FROM AUTHOR]

The main objective of the present work was to review the current knowledge about the factors that influence the different phases of the natural regeneration of maritime pine (Pinus pinaster Aiton) and propose scientifically based management schedules. The review focused on the natural regeneration of maritime pine within its most representative areas (Portugal, Spain, and France). First, a brief characterisation of the main phases of the natural regeneration of maritime pine is described. Next, information on the factors affecting the natural regeneration of the species is provided, highlighting its positive and negative effects. Finally, management proposals are presented to promote the natural regeneration of maritime pine species. Numerous factors influencing the natural regeneration of maritime pine were identified. Fires and climatic factors can intervene in all three regeneration phases (seeding, germination, and seedling survival and development). The natural regeneration failure of maritime pine species can be aggravated in drier scenarios. Forest management plays an important role as it can promote the natural regeneration of the species. [ABSTRACT FROM AUTHOR]

Forests are important because they contribute to biodiversity, regulation of carbon dioxide, protection of hydrographic basins, wood production. This article presents a methodology for fast and effective counting of treetops using the mathematical symmetry of the grayscale image. For the treetop counting, the unsupervised k-means classification Algorithm was used with two groups or centroids: treetop and not-treetop. By using these groups and the mathematical symmetry of the image, a fast k-means classification Algorithm is generated. To solve the problem of treetop overlapping and perform a more accurate counting, the watershed Algorithm was used. This methodology has a mean treetop count accuracy of 98.3% with a confidence level of 99% in the interval (97.31, 99.7). Aerial images of the coniferous forest of Alcudia, Mallorca, Spain were used. Forests attenuate climatic changes originated by global warming. Drastic climatic changes cause catastrophes to humanity. This research would help the automatic, massive and recurring counting of treetops with the aim of obtaining forest inventories in order to take care of forests. [ABSTRACT FROM AUTHOR]

Wildfires in Mediterranean regions have become a serious problem, and it is currently the main cause of forest loss. Numerous prediction methods have been applied worldwide to estimate future fire activity and area burned in order to provide a stable basis for future allocation of fire-fighting resources. The present study investigated the performance of an artificial neural network (ANN) in burned area size prediction and to assess the evolution of future wildfires and the area concerned under climate change in southern Spain. The study area comprised 39.41 km2 of land burned from 2000 to 2014. ANNs were used in two subsequential phases: classifying the size of the wildfires and predicting the burned surface for fires larger than 30,000 m2. Matrix of confusion and 10-fold cross-validations were used to evaluate ANN classification and mean absolute deviation, root mean square error, mean absolute percent error and bias, which were the metrics used for burned area prediction. The success rate achieved was above 60–70% depending on the zone. An average temperature increase of 3 °C and a 20% increase in wind speed during 2071–2100 results in a significant increase of the number of fires, up to triple the current figure, resulting in seven times the average yearly burned surface depending on the zone and the climate change scenario. [ABSTRACT FROM AUTHOR]

Climate change could pose a significant threat to the energy sector in various countries. The objective of this study is to analyze the long-term impact of changes in precipitation and water availability on hydroelectric production. To do so, the study focuses on three hydroelectric power plants in Southern Spain combining climatological, technical and economic data and projections. A physical model has been designed that reproduces the plants' operations and incorporates various scenarios for the evolution of contributions to the basin. The results predict a 10 to 49% drop in production by the end of the century, depending on the plant and scenario. This decrease in production, in accordance with our economic and operational hypotheses, would significantly affect the operating margins of the facilities and, in certain scenarios, could reach an economically unsustainable level by the end of the century. An investment analysis has been carried out as well, showing that climate change may jeopardize future investments in similar facilities. [ABSTRACT FROM AUTHOR]

Wetlands are among the most biologically active ecosystems on Earth, playing an important role in the global carbon cycle. Methane production in wetlands, resulting from anaerobic respiration of organic matter, accounts for an important part of natural sources of methane. In this work, we have evaluated the methane release rates of saline shallow lakes located in Central Spain, some of which maintain natural conditions, whereas others are hydrologically altered, with lowered salinity, or even presenting trophic alterations. We used sediment core plus water incubations to determine the release of methane from the studied lakes to the atmosphere, integrating both diffusion and ebullition processes, as well as the effects of temperature and salinity on methane production. The studied hypersaline lakes released methane at rates within the lowest range reported for temperate lakes and wetlands, whereas in hydrologically altered lakes that have dropped their salinity these rates were markedly higher. Models built with the specific response of methane release rates to temperature regarding the temperature changes expected according to the RCP climate scenarios predicted significant increases of these rates for the future, which could almost double current methane release for some of the studied lakes under the most pessimistic mitigation scenario (RCP8.5). [ABSTRACT FROM AUTHOR]

Simple Summary: Tuta absoluta is an invasive insect pest that has spread widely and established itself in many countries since its first detection in Spain in 2006. The devastating moth originates in South America and attacks tomato and other solanaceous vegetables, leading to huge losses in yield and potential income particularly for small-scale farmers who often lack the resources and knowledge to manage the pest. In most cases, farmers have resorted to the indiscriminate application of broad-spectrum synthetic pesticides, which in most cases are not registered and are often used at high doses. This has resulted in the pest developing resistance to most major classes of pesticides. In addition, the non-selective use of toxic pesticides has resulted in negative effects on the health of users, consumers, and non-target organisms such as pollinators and natural enemies of insect pests. Various tactics aimed at controlling T. absoluta have been developed and are at different stages of adoption by farmers. To ensure that they are effective, sustainable, and friendly to both users and the environment, there is a need for a comprehensive understanding of the pest's biology and ecology. To this effect, the present study developed models to predict intricate details of the pest's development, survival, and reproduction using data generated in laboratory studies. Among other important findings, the study reports that temperatures between 20–25 °C are ideal for the development, survival, reproduction, and increase in the population of T. absoluta. These findings are vital in developing strategies in managing the pest, especially in light of global climate change. The tomato leafminer, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is an invasive pest that devastates the production of tomatoes and other solanaceous vegetables. Since its trans-Atlantic invasion in 2006, T. absoluta has spread and established in many countries across the Afro-Eurasian Supercontinent, causing huge yield losses. This study aimed to determine the relationship between temperature and the life history traits of T. absoluta and provide the thermal thresholds for development using life cycle modelling. Linear and non-linear models were fitted to life table data collected at five constant temperatures of 15, 20, 25, 30, and 35 °C, with Relative Humidity 70 ± 5% and photoperiod 12L:12D. Another experiment was conducted at fluctuating temperatures to validate the laboratory results. Tuta absoluta completed its life cycle at temperatures between 15 and 35 °C. The development time ranged between 4.0–11 days, 6.3–16.0 days, and 5.4–20.7 days for egg, larva, and pupa, respectively. The lowest thermal threshold was estimated at 8.10, 7.83, and 11.62 °C, respectively for egg, larva, and pupa. While the optimum temperature for T. absoluta immature stages survival and female fecundity were predicted at a temperature range of 21–23 °C. The intrinsic rate of increase (rm), gross reproductive (GRR), and net reproductive (Ro) rates were significantly higher at temperatures between 20–25 °C. The model validation outcome showed similarities between observed and simulated values for development time, mortality rate, and life table parameters, attesting to the quality of the phenology model. Our results will help in predicting the effect of climate warming on the distribution and population dynamics of T. absoluta. Furthermore, the results could be used to develop management strategies adapted to different agroecological zones. [ABSTRACT FROM AUTHOR]

Since climate change projections contain many uncertainties and are normally unable to predict the direction and magnitude of change at the small scale needed by forest managers, some understanding about the functioning of the target forest should be obtained before a robust management strategy can be applied. Structure and regeneration patterns are related to key ecosystem processes which, on the other hand, can be modified by silvicultural treatments. In this research, the structure and recruitment dynamics of two stands with different histories of management were investigated in the southern limit of the range of Pinus nigra subsp. salzmannii (Southeast Spain). We described forest structure and facilitation effects by forest canopies and nurse shrubs, and quantified the processes affecting each stage of regeneration (dispersed seed, first year seedling and second year seedling) in different microhabitats. Forest structure was more complex in the stand scarcely influenced by human activities. Juniperus communis shrubs seemed to facilitate the establishment of tree saplings. Most seedlings died of desiccation during their first summer. At best, 190 out of 10,000 emerged seedlings survived the first summer. In light of these results, the possibilities of applying close-to-nature forestry in the study forests and other aspects of silviculture under a frame of adaptive forest management are discussed. [ABSTRACT FROM AUTHOR]

Climate change might entail significant alterations in future forest productivity, profitability and management. In this work, we estimated the financial profitability (Soil Expectation Value, SEV) of a set of radiata pine plantations in the northwest of Spain under climate change. We optimized silvicultural interventions using a differentiable approach and projected future productivity using a machine learning model basing on the climatic predictions of 11 Global Climate Models (GCMs) and two Representative Concentration Pathways (RCPs). The forecasted mean SEV for future climate was lower than current SEV (∼22% lower for RCP 4.5 and ∼29% for RCP 6.0, with interest rate = 3%). The dispersion of the future SEV distribution was very high, alternatively forecasting increases and decreases in profitability under climate change depending on the chosen GCM. Silvicultural optimization considering future productivity projections effectively mitigated the potential economic losses due to climate change; however, its ability to perform this mitigation was strongly dependent on interest rates. We conclude that the financial profitability of radiata pine plantations in this region might be significantly reduced under climate change, though further research is necessary for clearing the uncertainties regarding the high dispersion of profitability projections. [ABSTRACT FROM AUTHOR]

Time series of mean monthly temperature and total monthly precipitation are two of the climatic variables most easily obtained from weather station records. There are many studies analyzing historical series of these variables, particularly in the Spanish territory. In this study, the series of these two variables in 47 stations of the provincial capitals of mainland Spain were analyzed. The series cover time periods from the 1940s to 2013; the studies reviewed in mainland Spain go up to 2008. ARIMA models were used to represent their variation. In the preliminary phase of description and identification of the model, a study to detect possible trends in the series was carried out in an isolated manner. Significant trends were found in 15 of the temperature series, and there were trends in precipitation in only five of them. The results obtained for the trends are discussed with reference to those of other, more detailed studies in the different regions, confirming whether the same trend was maintained over time. With the ARIMA models obtained, 12-month predictions were made by measuring errors with the observed data. More than 50% of the series of both were modeled. Predictions with these models could be useful in different aspects of seasonal job planning, such as wildfires, pests and diseases, and agricultural crops. [ABSTRACT FROM AUTHOR]

Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. In this work, we propose a framework to evaluate the predictive capacity of 11 multi-model ensemble methods (MMEs), including random forest (RF), to estimate reference evapotranspiration (ET 0 ) using 10 AR5 models for the scenarios RCP4.5 and RCP8.5. The study was carried out in the Segura Hydrographic Demarcation (SE of Spain), a typical Mediterranean semiarid area. ET 0 was estimated in the historical scenario (1970–2000) using a spatially calibrated Hargreaves model. MMEs obtained better results than any individual model for reproducing daily ET 0 . In validation, RF resulted more accurate than other MMEs (Kling–Gupta efficiency (KGE) M = 0.903 , S D = 0.034 for KGE and M = 3.17 , S D = 2.97 for absolute percent bias). A statistically significant positive trend was observed along the 21st century for RCP8.5, but this trend stabilizes in the middle of the century for RCP4.5. The observed spatial pattern shows a larger ET 0 increase in headwaters and a smaller increase in the coast. [ABSTRACT FROM AUTHOR]

Simple Summary: In temperate zones of the Earth, most species reproduce in seasons providing the most favourable environmental conditions. Producing gametes is expensive in energetical terms, so both males and females either reduce or abolish gametogenesis during the non-breeding period. We thoroughly studied the testes of sexually inactive males of two rodents, the wood mouse, Apodemus sylvaticus, and the Algerian mouse, Mus spretus, in southern Iberian peninsula. These populations are syntopic, that is, animals of the two species share their territories and resources, so one would expect them to show similar or identical seasonal reproduction patterns. Contrarily, we found that both species reproduce during most of the year, but wood mice stop breeding in the summer whereas Algerian mice do it in winter. These divergent seasonal breeding patterns imply that either very subtle animal features and/or environmental cues operate to determine reproduction timing and support the notion that multiple models of circannual reproduction patterns are possible for different populations of the same species, showing that the mechanisms controlling seasonal reproduction are in fact very plastic and fast evolving. Hence, small mammals probably have multiple ways available to get adapted to the unstable environmental conditions derived from the ongoing global climate change. In most mammals with seasonal reproduction, males undergo testis regression during the non-breeding period. We performed a morphological, hormonal, functional, and molecular study of the testes of sexually inactive males of two species of murine rodents, the wood mouse, Apodemus sylvaticus, and the Algerian mouse, Mus spretus, in syntopic populations of southern Iberian peninsula. Both species reproduce during most of the year, but wood mice stop breeding in the summer whereas Algerian mice do it in winter. Sexually inactive males of A. sylvaticus show complete testis regression with reduced levels of serum testosterone and abnormal distribution of cell-adhesion molecules. Contrarily, inactive males of M. spretus maintain almost normal spermotogenesis despite a significant reduction of androgenic function. The lack of an evident explanation for the divergent seasonal breeding patterns found in southern populations of A. sylvaticus and M. spretus, compared with northern ones, implies that very subtle species/population-specific features and/or non-conspicuous environmental cues probably operate to determine their seasonal breeding pattern. These results also support the notion that multiple models of circannual testis variation are possible for different populations of the same species, showing that the mechanisms controlling seasonal reproduction are in fact very plastic and fast evolving. [ABSTRACT FROM AUTHOR]